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Bug fixes to do with array sizes.

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Incorporated eldads outer product code
This commit is contained in:
Rowan Cockett
2013-07-19 11:24:14 -07:00
parent c9dc29bf89
commit f626cedfb8
6 changed files with 96 additions and 104 deletions
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SimPEG/DiffOperators.py
+41 -34
View File
@@ -1,6 +1,16 @@
import numpy as np
from scipy import sparse
from sputils import ddx, sdiag, speye, kron3, spzeros, av
from scipy import sparse as sp
from sputils import sdiag, speye, kron3, spzeros
def ddx(n):
"""Define 1D derivatives"""
return sp.spdiags((np.ones((n+1, 1))*[-1, 1]).T, [0, 1], n, n+1, format="csr")
def av(n):
"""Define 1D averaging operator"""
return sp.spdiags((0.5*np.ones((n+1, 1))*[1, 1]).T, [0, 1], n, n+1, format="csr")
class DiffOperators(object):
@@ -16,20 +26,20 @@ class DiffOperators(object):
def fget(self):
if(self._faceDiv is None):
# The number of cell centers in each direction
n = [hk.size for hk in self.h]
n = self.n
# Compute faceDivergence operator on faces
dd = [ddx(k) for k in n]
if(self.dim == 1):
D = dd[0]
elif(self.dim == 2):
D1 = sparse.kron(speye(n[1]), dd[0])
D2 = sparse.kron(dd[1], speye(n[0]))
D = sparse.hstack((D1, D2), format="csr")
D1 = sp.kron(speye(n[1]), dd[0])
D2 = sp.kron(dd[1], speye(n[0]))
D = sp.hstack((D1, D2), format="csr")
elif(self.dim == 3):
D1 = kron3(speye(n[2]), speye(n[1]), dd[0])
D2 = kron3(speye(n[2]), dd[1], speye(n[0]))
D3 = kron3(dd[2], speye(n[1]), speye(n[0]))
D = sparse.hstack((D1, D2, D3), format="csr")
D = sp.hstack((D1, D2, D3), format="csr")
# Compute areas of cell faces
S = self.area
# Compute cell volumes
@@ -62,7 +72,7 @@ class DiffOperators(object):
D2 = kron3(speye(n3+1), d2, speye(n1+1))
D3 = kron3(d3, speye(n2+1), speye(n1+1))
G = sparse.vstack((D1, D2, D3), format="csr")
G = sp.vstack((D1, D2, D3), format="csr")
self._nodalGrad = sdiag(1/L)*G
return self._nodalGrad
return locals()
@@ -101,9 +111,9 @@ class DiffOperators(object):
O2 = spzeros(np.shape(D31)[0], np.shape(D32)[1])
O3 = spzeros(np.shape(D21)[0], np.shape(D13)[1])
C = sparse.vstack((sparse.hstack((O1, -D32, D23)),
sparse.hstack((D31, O2, -D13)),
sparse.hstack((-D21, D12, O3))), format="csr")
C = sp.vstack((sp.hstack((O1, -D32, D23)),
sp.hstack((D31, O2, -D13)),
sp.hstack((-D21, D12, O3))), format="csr")
self._edgeCurl = sdiag(1/S)*(C*sdiag(L))
return self._edgeCurl
@@ -116,18 +126,16 @@ class DiffOperators(object):
def fget(self):
if(self._faceAve is None):
# The number of cell centers in each direction
n1 = np.size(self.hx)
n2 = np.size(self.hy)
n3 = np.size(self.hz)
av1 = av(n1)
av2 = av(n2)
av3 = av(n3)
self._faceAve = sparse.hstack(kron3(speye(n3), speye(n2), av1),
kron3(speye(n3), av2, speye(n3)),
kron3(av3, speye(n2), speye(n3)), format="csr")
n = self.n
if(self.dim == 1):
self._faceAve = av(n[0])
elif(self.dim == 2):
self._faceAve = sp.hstack((sp.kron(speye(n[1]), av(n[0])),
sp.kron(av(n[1]), speye(n[0]))), format="csr")
elif(self.dim == 3):
self._faceAve = sp.hstack((kron3(speye(n[2]), speye(n[1]), av(n[0])),
kron3(speye(n[2]), av(n[1]), speye(n[0])),
kron3(av(n[2]), speye(n[1]), speye(n[0]))), format="csr")
return self._faceAve
return locals()
_faceAve = None
@@ -139,17 +147,16 @@ class DiffOperators(object):
def fget(self):
if(self._edgeAve is None):
# The number of cell centers in each direction
n1 = np.size(self.hx)
n2 = np.size(self.hy)
n3 = np.size(self.hz)
av1 = av(n1)
av2 = av(n2)
av3 = av(n3)
self._edgeAve = sparse.hstack(kron3(av3, av2, speye(n1)),
kron3(av3, speye(n2), av1),
kron3(speye(n3), av2, av1), format="csr")
n = self.n
if(self.dim == 1):
raise Exception('Edge Averaging does not make sense in 1D: Use Identity?')
elif(self.dim == 2):
self._edgeAve = sp.hstack((sp.kron(av(n[1]), speye(n[0])),
sp.kron(speye(n[1]), av(n[0]))), format="csr")
elif(self.dim == 3):
self._edgeAve = sp.hstack((kron3(av(n[2]), av(n[1]), speye(n[0])),
kron3(av(n[2]), speye(n[1]), av(n[0])),
kron3(speye(n[2]), av(n[1]), av(n[0]))), format="csr")
return self._edgeAve
return locals()
_edgeAve = None
SimPEG/TensorMesh.py
+22 -22
View File
@@ -22,15 +22,16 @@ class TensorMesh(BaseMesh, TensorView, DiffOperators):
"""
def __init__(self, h, x0=None):
super(TensorMesh, self).__init__(np.array([len(x) for x in h]), x0)
super(TensorMesh, self).__init__(np.array([x.size for x in h]), x0)
assert len(h) == len(self.x0), "Dimension mismatch. x0 != len(h)"
for i, h_i in enumerate(h):
assert type(h_i) == np.ndarray, ("h[%i] is not a numpy array." % i)
assert len(h_i.shape) == 1, ("h[%i] must be a 1D numpy array." % i)
# Ensure h contains 1D vectors
self._h = [x.ravel() for x in h]
self._h = [mkvc(x) for x in h]
def h():
doc = "h is a list containing the cell widths of the tensor mesh in each dimension."
@@ -193,17 +194,16 @@ class TensorMesh(BaseMesh, TensorView, DiffOperators):
def fget(self):
if(self._vol is None):
vh = [mkvc(x, 2) for x in self.h]
vh = self.h
# Compute cell volumes
if(self.dim == 1):
self._vol = mkvc(vh[0])
elif(self.dim == 2):
# Cell sizes in each direction
self._vol = mkvc(vh[0]*vh[1].T)
self._vol = mkvc(np.outer(vh[0], vh[1]))
elif(self.dim == 3):
# Cell sizes in each direction
v12 = vh[0]*vh[1].T
self._vol = mkvc(mkvc(v12, 2)*vh[2].T)
self._vol = mkvc(np.outer(mkvc(np.outer(vh[0], vh[1])), vh[2]))
return self._vol
return locals()
_vol = None
@@ -215,20 +215,20 @@ class TensorMesh(BaseMesh, TensorView, DiffOperators):
def fget(self):
if(self._area is None):
# Ensure that we are working with column vectors
vh = [mkvc(x, 2) for x in self.h]
vh = self.h
# The number of cell centers in each direction
n = [x.size for x in self.h]
n = self.n
# Compute areas of cell faces
if(self.dim == 1):
self._area = np.ones((n[0]+1, 1))
self._area = np.ones(n[0]+1)
elif(self.dim == 2):
area1 = np.ones((n[0]+1, 1))*vh[1].T
area2 = vh[0]*np.ones((n[1]+1, 1)).T
area1 = np.outer(np.ones(n[0]+1), vh[1])
area2 = np.outer(vh[0], np.ones(n[1]+1))
self._area = np.r_[mkvc(area1), mkvc(area2)]
elif(self.dim == 3):
area1 = np.ones((n[0]+1, 1))*mkvc(vh[1]*vh[2].T)
area2 = vh[0]*mkvc(np.ones((n[1]+1, 1))*vh[2].T)
area3 = vh[0]*mkvc(vh[1]*np.ones((n[2]+1, 1)).T)
area1 = np.outer(np.ones(n[0]+1), mkvc(np.outer(vh[1], vh[2])))
area2 = np.outer(vh[0], mkvc(np.outer(np.ones(n[1]+1), vh[2])))
area3 = np.outer(vh[0], mkvc(np.outer(vh[1], np.ones(n[2]+1))))
self._area = np.r_[mkvc(area1), mkvc(area2), mkvc(area3)]
return self._area
return locals()
@@ -239,22 +239,22 @@ class TensorMesh(BaseMesh, TensorView, DiffOperators):
doc = "Construct edge legnths of the 3D model as 1d array."
def fget(self):
if(self._area is None):
if(self._edge is None):
# Ensure that we are working with column vectors
vh = [mkvc(x, 2) for x in self.h]
vh = self.h
# The number of cell centers in each direction
n = [x.size for x in self.h]
n = self.n
# Compute edge lengths
if(self.dim == 1):
self._edge = mkvc(vh[0])
elif(self.dim == 2):
l1 = vh[0]*np.ones((n[1]+1, 1)).T
l2 = np.ones((n[0]+1, 1))*vh[1].T
l1 = np.outer(vh[0], np.ones(n[1]+1))
l2 = np.outer(np.ones(n[0]+1), vh[1])
self._edge = np.r_[mkvc(l1), mkvc(l2)]
elif(self.dim == 3):
l1 = vh[0]*mkvc(np.ones((n[1]+1, 1))*np.ones((n[2]+1, 1)).T)
l2 = np.ones((n[0]+1, 1))*mkvc(vh[1]*np.ones((n[2]+1, 1)).T)
l3 = np.ones((n[0]+1, 1))*mkvc(np.ones((n[1]+1, 1))*vh[2].T)
l1 = np.outer(vh[0], mkvc(np.outer(np.ones(n[1]+1), np.ones(n[2]+1))))
l2 = np.outer(np.ones(n[0]+1), mkvc(np.outer(vh[1], np.ones(n[2]+1))))
l3 = np.outer(np.ones(n[0]+1), mkvc(np.outer(np.ones(n[1]+1), vh[2])))
self._edge = np.r_[mkvc(l1), mkvc(l2), mkvc(l3)]
return self._edge
return locals()
SimPEG/sputils.py
+13 -26
View File
@@ -1,43 +1,30 @@
import numpy as np
from scipy import sparse
from numpy import ones
from scipy import sparse as sp
def ddx(n):
"""Define 1D derivatives"""
return sparse.spdiags((np.ones((n+1,1))*[-1,1]).T, [0,1], n, n+1, format="csr")
def sdiag(h):
"""Sparse diagonal matrix"""
return sparse.spdiags(h, 0, np.size(h), np.size(h), format="csr")
return sp.spdiags(h, 0, np.size(h), np.size(h), format="csr")
def speye(n):
"""Sparse identity"""
return sparse.identity(n, format="csr")
return sp.identity(n, format="csr")
def kron3(A, B, C):
"""Two kron prods"""
return sparse.kron(sparse.kron(A, B), C, format="csr")
return sp.kron(sp.kron(A, B), C, format="csr")
def spzeros(n1, n2):
"""spzeros"""
return sparse.coo_matrix((n1, n2)).tocsr()
return sp.coo_matrix((n1, n2)).tocsr()
def av(n):
"""Define 1D averaging operator"""
return sparse.spdiags((0.5*np.ones((n+1,1))*[1,1]).T, [0,1], n, n+1, format="csr")
def av(n):
"""Define 1D average"""
return 0.5*(sparse.spdiags(ones(n+1), 0, n, n+1) + sparse.spdiags(ones(n+1), 1, n, n+1))
def spzeros(n1, n2):
"""spzeros"""
return sparse.coo_matrix((n1, n2))
def appendBottom(A, B):
"""append on bottom"""
C = sparse.vstack((A, B))
C = sp.vstack((A, B))
C = C.tocsr()
return C
@@ -51,7 +38,7 @@ def appendBottom3(A, B, C):
def appendRight(A, B):
"""append on right"""
C = sparse.hstack((A, B))
C = sp.hstack((A, B))
C = C.tocsr()
return C
@@ -65,9 +52,9 @@ def appendRight3(A, B, C):
def blkDiag(A, B):
"""blockdigonal"""
O12 = sparse.coo_matrix((np.shape(A)[0], np.shape(B)[1]))
O21 = sparse.coo_matrix((np.shape(B)[0], np.shape(A)[1]))
C = sparse.vstack((sparse.hstack((A, O12)), sparse.hstack((O21, B))))
O12 = sp.coo_matrix((np.shape(A)[0], np.shape(B)[1]))
O21 = sp.coo_matrix((np.shape(B)[0], np.shape(A)[1]))
C = sp.vstack((sp.hstack((A, O12)), sp.hstack((O21, B))))
C = C.tocsr()
return C
SimPEG/tests/test_curl.py
+6 -7
View File
@@ -11,12 +11,11 @@ for i in range(4):
icount=i+1
nc = 2**icount
# Define the mesh
h1 = np.ones((1,nc))/nc
h2 = np.ones((1,nc))/nc
h3 = np.ones((1,nc))/nc
h1 = np.ones(nc)/nc
h2 = np.ones(nc)/nc
h3 = np.ones(nc)/nc
h = [h1, h2, h3]
x0 = np.zeros((3, 1))
M = TensorMesh(h, x0)
M = TensorMesh(h)
#n = M.plotGrid()
# Generate DIV matrix
@@ -41,7 +40,7 @@ for i in range(4):
if icount == 1:
print 'h | inf norm | error ratio'
print '---------------------------------------'
print '%6.4f | %8.2e |'% (h1[0,0], err)
print '%6.4f | %8.2e |'% (h1[0], err)
else:
print '%6.4f | %8.2e | %6.4f' % (h1[0,0], err, err_old/err)
print '%6.4f | %8.2e | %6.4f' % (h1[0], err, err_old/err)
err_old = err
SimPEG/tests/test_div.py
+8 -8
View File
@@ -11,9 +11,9 @@ for i in range(4):
icount=i+1
nc = 2**icount
# Define the mesh
h1 = np.ones((1,nc))/nc
h2 = np.ones((1,nc))/nc
h3 = np.ones((1,nc))/nc
h1 = np.ones(nc)/nc
h2 = np.ones(nc)/nc
h3 = np.ones(nc)/nc
h = [h1, h2, h3]
x0 = np.zeros((3, 1))
M = TensorMesh(h, x0)
@@ -24,9 +24,9 @@ for i in range(4):
#Test function
fun = lambda x: np.sin(x)
Fx = fun(M.gridFx[:,0])
Fy = fun(M.gridFy[:,1])
Fz = fun(M.gridFz[:,2])
Fx = fun(M.gridFx[:, 0])
Fy = fun(M.gridFy[:, 1])
Fz = fun(M.gridFz[:, 2])
F = np.concatenate((Fx,Fy,Fz))
divF = DIV*F
@@ -39,7 +39,7 @@ for i in range(4):
if icount == 1:
print 'h | inf norm | error ratio'
print '---------------------------------------'
print '%6.4f | %8.2e |'% (h1[0,0], err)
print '%6.4f | %8.2e |'% (h1[0], err)
else:
print '%6.4f | %8.2e | %6.4f' % (h1[0,0], err, err_old/err)
print '%6.4f | %8.2e | %6.4f' % (h1[0], err, err_old/err)
err_old = err
SimPEG/tests/test_grad.py
+6 -7
View File
@@ -11,12 +11,11 @@ for i in range(4):
icount=i+1
nc = 2**icount
# Define the mesh
h1 = np.ones((1,nc))/nc
h2 = np.ones((1,nc))/nc
h3 = np.ones((1,nc))/nc
h1 = np.ones(nc)/nc
h2 = np.ones(nc)/nc
h3 = np.ones(nc)/nc
h = [h1, h2, h3]
x0 = np.zeros((3, 1))
M = TensorMesh(h, x0)
M = TensorMesh(h)
#n = M.plotGrid()
# Generate DIV matrix
@@ -38,8 +37,8 @@ for i in range(4):
if icount == 1:
print 'h | inf norm | error ratio'
print '---------------------------------------'
print '%6.4f | %8.2e |'% (h1[0,0], err)
print '%6.4f | %8.2e |'% (h1[0], err)
else:
print '%6.4f | %8.2e | %6.4f' % (h1[0,0], err, err_old/err)
print '%6.4f | %8.2e | %6.4f' % (h1[0], err, err_old/err)
err_old = err